Canada has a wide range of landslide types reflecting the diverse geomorphic
and geologic environments in the nation’s landscape. Many civil engineering
projects are located on or near sloping ground, and thus are potentially
subject to various kinds of slope instability, which often produces
extensive property damage and occasionally loss of life. A typical example
is the massive landslide occurred on the Nipigon River, north of the town of
Nipigon, Ontario in the 1990, which involved an estimated 300,000 cubic
meters of soil and extended almost 350m inshore with a maximum width
of approximately 290m.
The traditional methods for slope stability investigation are reliant on
deterministic approaches which involve an overall factor of safety to account
for various uncertainties. It is found that critical geotechnical parameters
such as shear strength parameters may be regarded as random variables
respectively with a probability distribution rather than deterministic
values or constants. In this research, an alternative approach of probabilistic
reliability method is adopted in slope engineering, which allows for systematic
analysis of uncertainties and for their inclusion in evaluating slope
performance. The research focuses on entropy-based reliability analysis
and design in slope engineering. The four sub topics are:
1. Introducing soil variables field testing by the vane shear test.
2. Proposing an entropy-based distribution free modelling for soil variables.
3. Developing a new reliability analysis method using entropy distributions.
4. Application of approach in the Nipigon slope’s analysis & design.
Firstly, the research involves the application of the vane shear test on the
Nipigon slope to obtain values of undrained shear strength (Su). Moreover,
the research proposes an entropy-based distribution-free method for
modeling of soil variables, using the combination of the maximum entropy
formalism (MEF) and Akaike information criterion (AIC). The method is
applied to generate the unbiased model for soil variables based on optimalorder
moments from soil samples. The method can adjust the level of sophistication
of the resulting probability as per the nature and quantity of
data. Its application on soil data of the slope of the Nipigon River landslide
area yields efficient results with the 3rd order being the optimal order
representing the quantified information very precisely.
Further, the research introduces a new reliability method to conduct a
reliability analysis of the Nipigon slope. The approach involves the modification
of the first-order reliability method to consider the non-normal
variables of the entropy distributions adequately, supported by GEO-Slope
software model analysis and response surface method to develop an explicit
performance function. The approach developed can incorporate the
uncertainties effectively and proficiently. The results imply that the Nipigon
slope is hazardous with a probability of failure value touching 40%. The
comparison of the proposed modified FORM with the GEO-Slope based
Monte Carlo simulation indicated similarities in the results, consequently
certifying the efficiency of the proposed algorithm.
Ultimately, a reliability-based slope is designed for the Nipigon slope
by implementing the proposed methodology. In the first case, pile reinforcement
is applied to the failure slope to enhance the stability of the failure
slope. However, the results display a spike in the reliability index, but
the slope is found unstable. Therefore, the slope is redesigned by creating a
homogeneous layer aided with pile reinforcement. The design reduces the
probability of failure up to 10-6, thereby making it stable.